lsst.meas.astrom gaf95d0f0f9+e66c719481
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fitTanSipWcs.py
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1# This file is part of meas_astrom.
2#
3# Developed for the LSST Data Management System.
4# This product includes software developed by the LSST Project
5# (https://www.lsst.org).
6# See the COPYRIGHT file at the top-level directory of this distribution
7# for details of code ownership.
8#
9# This program is free software: you can redistribute it and/or modify
10# it under the terms of the GNU General Public License as published by
11# the Free Software Foundation, either version 3 of the License, or
12# (at your option) any later version.
13#
14# This program is distributed in the hope that it will be useful,
15# but WITHOUT ANY WARRANTY; without even the implied warranty of
16# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
17# GNU General Public License for more details.
18#
19# You should have received a copy of the GNU General Public License
20# along with this program. If not, see <https://www.gnu.org/licenses/>.
21
22__all__ = ["FitTanSipWcsTask", "FitTanSipWcsConfig"]
23
24
25import numpy as np
26
27import lsst.geom
28import lsst.sphgeom
29import lsst.afw.geom as afwGeom
30import lsst.afw.table as afwTable
31import lsst.pex.config as pexConfig
32import lsst.pipe.base as pipeBase
33from .setMatchDistance import setMatchDistance
34from .sip import makeCreateWcsWithSip
35
36
37class FitTanSipWcsConfig(pexConfig.Config):
38 """Config for FitTanSipWcsTask."""
39 order = pexConfig.RangeField(
40 doc="order of SIP polynomial",
41 dtype=int,
42 default=2,
43 min=0,
44 )
45 numIter = pexConfig.RangeField(
46 doc="number of iterations of fitter (which fits X and Y separately, and so benefits from "
47 "a few iterations",
48 dtype=int,
49 default=3,
50 min=1,
51 )
52 numRejIter = pexConfig.RangeField(
53 doc="number of rejection iterations",
54 dtype=int,
55 default=1,
56 min=0,
57 )
58 rejSigma = pexConfig.RangeField(
59 doc="Number of standard deviations for clipping level",
60 dtype=float,
61 default=3.0,
62 min=0.0,
63 )
64 maxScatterArcsec = pexConfig.RangeField(
65 doc="maximum median scatter of a WCS fit beyond which the fit fails (arcsec); "
66 "be generous, as this is only intended to catch catastrophic failures",
67 dtype=float,
68 default=10,
69 min=0,
70 )
71
72
73class FitTanSipWcsTask(pipeBase.Task):
74 """Fit a TAN-SIP WCS given a list of reference object/source matches.
75 """
76 ConfigClass = FitTanSipWcsConfig
77 _DefaultName = "fitWcs"
78
79 @pipeBase.timeMethod
80 def fitWcs(self, matches, initWcs, bbox=None, refCat=None, sourceCat=None, exposure=None):
81 """Fit a TAN-SIP WCS from a list of reference object/source matches
82
83 Parameters
84 ----------
85 matches : `list` of `lsst.afw.table.ReferenceMatch`
86 The following fields are read:
87
88 - match.first (reference object) coord
89 - match.second (source) centroid
90
91 The following fields are written:
92
93 - match.first (reference object) centroid,
94 - match.second (source) centroid
95 - match.distance (on sky separation, in radians)
96
97 initWcs : `lsst.afw.geom.SkyWcs`
98 initial WCS
99 bbox : `lsst.geom.Box2I`
100 the region over which the WCS will be valid (an lsst:afw::geom::Box2I);
101 if None or an empty box then computed from matches
103 reference object catalog, or None.
104 If provided then all centroids are updated with the new WCS,
105 otherwise only the centroids for ref objects in matches are updated.
106 Required fields are "centroid_x", "centroid_y", "coord_ra", and "coord_dec".
107 sourceCat : `lsst.afw.table.SourceCatalog`
108 source catalog, or None.
109 If provided then coords are updated with the new WCS;
110 otherwise only the coords for sources in matches are updated.
111 Required fields are "slot_Centroid_x", "slot_Centroid_y", and "coord_ra", and "coord_dec".
112 exposure : `lsst.afw.image.Exposure`
113 Ignored; present for consistency with FitSipDistortionTask.
114
115 Returns
116 -------
117 result : `lsst.pipe.base.Struct`
118 with the following fields:
119
120 - ``wcs`` : the fit WCS (`lsst.afw.geom.SkyWcs`)
121 - ``scatterOnSky`` : median on-sky separation between reference
122 objects and sources in "matches" (`lsst.afw.geom.Angle`)
123 """
124 if bbox is None:
125 bbox = lsst.geom.Box2I()
126
127 import lsstDebug
128 debug = lsstDebug.Info(__name__)
129
130 wcs = self.initialWcs(matches, initWcs)
131 rejected = np.zeros(len(matches), dtype=bool)
132 for rej in range(self.config.numRejIter):
133 sipObject = self._fitWcs([mm for i, mm in enumerate(matches) if not rejected[i]], wcs)
134 wcs = sipObject.getNewWcs()
135 rejected = self.rejectMatches(matches, wcs, rejected)
136 if rejected.sum() == len(rejected):
137 raise RuntimeError("All matches rejected in iteration %d" % (rej + 1,))
138 self.log.debug(
139 "Iteration {0} of astrometry fitting: rejected {1} outliers, "
140 "out of {2} total matches.".format(
141 rej, rejected.sum(), len(rejected)
142 )
143 )
144 if debug.plot:
145 print("Plotting fit after rejection iteration %d/%d" % (rej + 1, self.config.numRejIter))
146 self.plotFit(matches, wcs, rejected)
147 # Final fit after rejection
148 sipObject = self._fitWcs([mm for i, mm in enumerate(matches) if not rejected[i]], wcs)
149 wcs = sipObject.getNewWcs()
150 if debug.plot:
151 print("Plotting final fit")
152 self.plotFit(matches, wcs, rejected)
153
154 if refCat is not None:
155 self.log.debug("Updating centroids in refCat")
156 afwTable.updateRefCentroids(wcs, refList=refCat)
157 else:
158 self.log.warn("Updating reference object centroids in match list; refCat is None")
159 afwTable.updateRefCentroids(wcs, refList=[match.first for match in matches])
160
161 if sourceCat is not None:
162 self.log.debug("Updating coords in sourceCat")
163 afwTable.updateSourceCoords(wcs, sourceList=sourceCat)
164 else:
165 self.log.warn("Updating source coords in match list; sourceCat is None")
166 afwTable.updateSourceCoords(wcs, sourceList=[match.second for match in matches])
167
168 self.log.debug("Updating distance in match list")
169 setMatchDistance(matches)
170
171 scatterOnSky = sipObject.getScatterOnSky()
172
173 if scatterOnSky.asArcseconds() > self.config.maxScatterArcsec:
174 raise pipeBase.TaskError(
175 "Fit failed: median scatter on sky = %0.3f arcsec > %0.3f config.maxScatterArcsec" %
176 (scatterOnSky.asArcseconds(), self.config.maxScatterArcsec))
177
178 return pipeBase.Struct(
179 wcs=wcs,
180 scatterOnSky=scatterOnSky,
181 )
182
183 def initialWcs(self, matches, wcs):
184 """Generate a guess Wcs from the astrometric matches
185
186 We create a Wcs anchored at the center of the matches, with the scale
187 of the input Wcs. This is necessary because matching returns only
188 matches with no estimated Wcs, and the input Wcs is a wild guess.
189 We're using the best of each: positions from the matches, and scale
190 from the input Wcs.
191
192 Parameters
193 ----------
194 matches : `list` of `lsst.afw.table.ReferenceMatch`
195 List of sources matched to references.
197 Current WCS.
198
199 Returns
200 -------
201 newWcs : `lsst.afw.geom.SkyWcs`
202 Initial WCS guess from estimated crpix and crval.
203 """
204 crpix = lsst.geom.Extent2D(0, 0)
205 crval = lsst.sphgeom.Vector3d(0, 0, 0)
206 for mm in matches:
207 crpix += lsst.geom.Extent2D(mm.second.getCentroid())
208 crval += mm.first.getCoord().getVector()
209 crpix /= len(matches)
210 crval /= len(matches)
211 newWcs = afwGeom.makeSkyWcs(crpix=lsst.geom.Point2D(crpix),
212 crval=lsst.geom.SpherePoint(crval),
213 cdMatrix=wcs.getCdMatrix())
214 return newWcs
215
216 def _fitWcs(self, matches, wcs):
217 """Fit a Wcs based on the matches and a guess Wcs.
218
219 Parameters
220 ----------
221 matches : `list` of `lsst.afw.table.ReferenceMatch`
222 List of sources matched to references.
224 Current WCS.
225
226 Returns
227 -------
229 Fitted SIP object.
230 """
231 for i in range(self.config.numIter):
232 sipObject = makeCreateWcsWithSip(matches, wcs, self.config.order)
233 wcs = sipObject.getNewWcs()
234 return sipObject
235
236 def rejectMatches(self, matches, wcs, rejected):
237 """Flag deviant matches
238
239 We return a boolean numpy array indicating whether the corresponding
240 match should be rejected. The previous list of rejections is used
241 so we can calculate uncontaminated statistics.
242
243 Parameters
244 ----------
245 matches : `list` of `lsst.afw.table.ReferenceMatch`
246 List of sources matched to references.
248 Fitted WCS.
249 rejected : array-like of `bool`
250 Array of matches rejected from the fit. Unused.
251
252 Returns
253 -------
254 rejectedMatches : `ndarray` of type `bool`
255 Matched objects found to be outside of tolerance.
256 """
257 fit = [wcs.skyToPixel(m.first.getCoord()) for m in matches]
258 dx = np.array([ff.getX() - mm.second.getCentroid().getX() for ff, mm in zip(fit, matches)])
259 dy = np.array([ff.getY() - mm.second.getCentroid().getY() for ff, mm in zip(fit, matches)])
260 good = np.logical_not(rejected)
261 return (dx > self.config.rejSigma*dx[good].std()) | (dy > self.config.rejSigma*dy[good].std())
262
263 def plotFit(self, matches, wcs, rejected):
264 """Plot the fit
265
266 We create four plots, for all combinations of (dx, dy) against
267 (x, y). Good points are black, while rejected points are red.
268
269 Parameters
270 ----------
271 matches : `list` of `lsst.afw.table.ReferenceMatch`
272 List of sources matched to references.
274 Fitted WCS.
275 rejected : array-like of `bool`
276 Array of matches rejected from the fit.
277 """
278 try:
279 import matplotlib.pyplot as plt
280 except ImportError as e:
281 self.log.warn("Unable to import matplotlib: %s", e)
282 return
283
284 fit = [wcs.skyToPixel(m.first.getCoord()) for m in matches]
285 x1 = np.array([ff.getX() for ff in fit])
286 y1 = np.array([ff.getY() for ff in fit])
287 x2 = np.array([m.second.getCentroid().getX() for m in matches])
288 y2 = np.array([m.second.getCentroid().getY() for m in matches])
289
290 dx = x1 - x2
291 dy = y1 - y2
292
293 good = np.logical_not(rejected)
294
295 figure = plt.figure()
296 axes = figure.add_subplot(2, 2, 1)
297 axes.plot(x2[good], dx[good], 'ko')
298 axes.plot(x2[rejected], dx[rejected], 'ro')
299 axes.set_xlabel("x")
300 axes.set_ylabel("dx")
301
302 axes = figure.add_subplot(2, 2, 2)
303 axes.plot(x2[good], dy[good], 'ko')
304 axes.plot(x2[rejected], dy[rejected], 'ro')
305 axes.set_xlabel("x")
306 axes.set_ylabel("dy")
307
308 axes = figure.add_subplot(2, 2, 3)
309 axes.plot(y2[good], dx[good], 'ko')
310 axes.plot(y2[rejected], dx[rejected], 'ro')
311 axes.set_xlabel("y")
312 axes.set_ylabel("dx")
313
314 axes = figure.add_subplot(2, 2, 4)
315 axes.plot(y2[good], dy[good], 'ko')
316 axes.plot(y2[rejected], dy[rejected], 'ro')
317 axes.set_xlabel("y")
318 axes.set_ylabel("dy")
319
320 plt.show()
def fitWcs(self, matches, initWcs, bbox=None, refCat=None, sourceCat=None, exposure=None)
Definition: fitTanSipWcs.py:80
def plotFit(self, matches, wcs, rejected)
def rejectMatches(self, matches, wcs, rejected)
Measure the distortions in an image plane and express them a SIP polynomials.
void updateRefCentroids(geom::SkyWcs const &wcs, ReferenceCollection &refList)
void updateSourceCoords(geom::SkyWcs const &wcs, SourceCollection &sourceList)
STL namespace.